An Exploration of Pursuing Professional Explorations

My Data Science Job Search: August - November, 2020 & December 2020 - Present

Rohan Lewis

2020.09.29 (Last Update 2020.02.16)

I began applying for Information Technology jobs on August 11th, 2020. I used LinkedIn as my primary source of information. I varied between large and small companies, EasyApply and normal applications via company job application portals or website submissions, and various locations across the US. I even applied to a job in Sydney, Australia (by accident) and a job in Toronto, Canada.

I took a break from 2020.11.06 - 2020.12.17.

I saved my application information in an Excel Spreadsheet as I applied. I decided to use it to practice some visualization techniques.

Job Title

This section looks at the specific job titles.

  1. I eliminated all non alphabetical characters.

  2. A recurring theme in job titles was numbering, such as "Data Analyst II" or "Data Scientist III". Since I had already eliminated numbers, I needed to eliminate Roman Numerals (only I, II, and III).

  3. I had some false negatives, so I fixed those.
    1. "AR VR" was changed back to "AR/VR" for one title.
    2. "C C" was changed back to "C2C" for one title.
    3. "Microsoft" was changed to "Microsoft-365" for one title.
    4. "Non IT" was changed back to "Non-IT" for one title.

  4. Words were then tallied.

Word Frequencies

Below are the top 10 and bottom 10 (some of the single occuring) words from the job titles.

Word Cloud

I thought a word cloud would be a fun representation to look at the job titles. The proportional size has been rescaled.

Companies

Some companies are hiring heavily. Some are recruiting and staffing agencies for others.

Once my application was in a system on a particular company's career portal page, it was easy to reapply. I used this quite a bit for companies like Amazon, Google, MITRE, and PayPal.

I used LinkedIn's EasyApply for many applications as well.

For the others, I sometimes applied as a guest, sometimes only had to upload my resume and cover, sometimes had to go through a 20 minute ordeal just for one opening. It varied. ¯_( ͡° ͜ʖ ͡°)_/¯ .

Company Applications by Date

See Appendix for full table of cumulative applications by company and date, sorted alphabetically and chronologically, respectively.

Bar Chart Race

Below is an animation of the above data. Bar chart races run more smoothly with larger numbers, like population, or monetary amounts, over longer periods of time. But I am happy the way this turned out.

Job Location

Some slight modifications were made from LinkedIn data during the application process:

  1. For Curate Partners, a job location was changed from Raleigh-Durham-Chapel Hill Area to Raleigh.
  2. For Parker & Lynch, a job location was changed from Orange County to Los Angeles.
  3. For Synectics, a job location was changed from Greater Chicago to Chicago.
  4. For several companies, job locations were changed from "San Francisco Bay Area" to "San Francisco".
  5. For several companies, job locations were changed from "Greater" or "Metropolitan" of a city to that city.
  6. For several companies, job locations were changed from "Washington DC-Baltimore Area" to either "Washington DC" or "Baltimore".

In addition, for Common App, the job location was changed from none specified to Arlington. I did not learn about their opening from LinkedIn.

By City

Remote Locations

Several jobs were advertised with no city, only remote.

I retrieved their office locations and manually entered them.

Missing Cities

Several jobs I applied to were in cities not in the spreadsheet I downloaded.

Manual Removal and Entry

Two were from Australia and one from Canada. For the others, I retrieved values from Google. An approximate average value was chosen for Dallas-Ft. Worth.

Chevy Chase

The left join was off. I soon determined that Chevy Chase, MD was repeated for some reason.

Mountain View

In addition, two cities in California are named Mountain View.

All cities, with their state, number of applications, and location, are displayed below.

By State

See Appendix for frequency by state.

US Map

Below is an interactive map of the US. Applications are sorted by city and state.

Waffle Plot

Below is the distribution of applications by state.

Appendix

Company Applications by Date

State Frequency